直线开关磁阻电机单神经元智能位置控制

Single Neuron Intelligent Position Control of Linear Switched Reluctance Motor

针对直线开关磁阻电机复杂非线性系统存在参数不确定、摩擦及外部扰动现象,提出一种基于果蝇优化算法(FOA)的智能位置跟踪控制策略。首先,引出直线开关磁阻电机的结构及数学模型;其次,对其运动模型进行空间离散化,并设计单神经元自适应控制器,神经元的权值通过果蝇优化算法进行在线自适应调整,实现对参数变化及外部扰动的抑制;最后通过仿真实验将论文方案与经典PID控制进行比较,仿真结果验证了论文方案具有更好的跟踪性能和对不确定扰动的鲁棒性。

Fruit fly optimization algorithm(FOA)based intelligent position tracking control scheme is proposed to solve the problem of parameter uncertainty,friction and external disturbance in the complex nonlinear system of linear switch reluctance mo⁃tor.Firstly,the structure and mathematical model of the linear switch reluctance motor are introduced.Secondly,the motion model is discretized and a single neuron adaptive controller is designed.The weight of the neuron is adjusted online through FOA to sup⁃press the parameter changes and external disturbances.Simulation results show that the presented scheme has better tracking perfor⁃mance and robustness to uncertain disturbance than classical PID control.